By migrating their databases to Azure, customers like Ernst and Young are modernizing their data estate and leveraging cutting-edge cloud innovations. However, the migration process can be complex, whether moving within the same database management system (homogeneous) or between different systems (heterogeneous). Microsoft offers a suite of tools for migration to simplify the migration process. To further enhance the user experience, we are streamlining the Azure database migration tools ecosystem. This involves retiring certain overlapping tools to simplify finding the right tool and provide unified migration experiences across all phases of migration. As part of this effort, effective 12/15/2024 we are replacing some tools with unified experiences that offer capabilities across various migration stages in the drive to modernize their data estate and take advantage of innovation in the cloud.

Azure Database Migration Guides

Step-by-step guidance for modernizing your data assets

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With a refined set of tools, you can confidently plan, assess, and execute your database migration with minimal downtime, ensuring a smooth transition to Azure SQL. Post the 12/15/24, retirement date, Microsoft will stop supporting these tools for any issues that arise and will not issue any bug fixes or further updates. Here is the list of tools that are planned for retirement and Microsoft recommended replacement tools.

Microsoft recommended tools for migration to Azure SQL

With the retirement of Database Migration Assistant for Oracle (DMAO), Database Schema Conversion Toolkit (DSCT), Data Access Migration Toolkit (DAMT), Database Experimentation Assistant (DEA), the Azure database migration tooling ecosystem is greatly simplified. Here is Microsoft’s recommendation for database migration tools for customers moving to Azure SQL. 

Homogenous migrations (SQL Server to Azure SQL) 

If the SQL Server that will be migrated is already enabled by Azure Arc, you can use Arc capabilities to perform a migration assessment and get optimal Azure SQL Target recommendations. Additionally, SQL Server enabled by Azure Arc provides multiple Azure benefits to SQL Servers outside Azure like automated backups and patching, Microsoft Defender for SQL, inventory of instances and databases, and Entra ID support. By enabling these Arc features, you can leverage cloud automation and security for Azure SQL Server even before you migrate. 

If the SQL Server outside Azure is not inventoried yet, you can use Azure Migrate for discovery, assessment and business case to know the right Azure SQL targets for your on-premises SQL Workloads and to get the projected cost savings of migrating to Azure SQL.

To migrate SQL Server into an Azure Virtual Machine with the same configuration as the source, users can use Azure Migrate to perform lift and shift migrations. SQL Server on Azure Virtual Machines allows you to easily migrate your SQL Server workloads to the cloud, offering SQL Server’s performance and security along with Azure’s flexibility and hybrid connectivity to address urgent business needs. Later you can evaluate one of the Azure SQL PaaS targets (Azure SQL Managed Instance, Azure SQL Database) and modernize to a PaaS service for better cost and workload performance optimizations. 

If you have completed an assessment and are ready to move to Azure SQL Managed Instance or Azure SQL Database, you can start your migration journey with Azure Migrate, you can use Azure Database Migration service or Azure SQL Migration extension for Azure Data Studio can be used. 

If the SQL Server estate is already inventoried, users can use Azure SQL Migration extension for Azure Data Studio to complete the entire migration journey i.e., perform assessment, get Azure SQL Target recommendations and perform migrations.

Heterogenous migrations (non-SQL Server databases to Azure SQL) 

With the availability of Target Assessment and SKU recommendation capabilities in SQL Server Migration Assistant (SSMA) along with existing code conversion and migration capabilities, SSMA becomes a single tool that you need to use to migrate from other source database platforms like Oracle, DB2, SAP ASE, MySQL, Access to Azure SQL or SQL Server. 

Learn more about modernizing your databases with Azure

• Get step-by-step guidance for modernizing your Oracle and SQL Server databases to Azure in the Azure Database Migration Guides.
• Read about the Azure Migrate Assessment for Azure SQL to get an overview of SQL Server assessment process using Azure Migrate.
• Know how to complete end to end SQL Server to Azure SQL migration journey with Azure SQL Migration extension for Azure Data Studio. 
• Find documentation for SQL Server Migration Assistant (SSMA), a tool for assessing and automating migration from Microsoft Access, DB2, MySQL, Oracle, and SAP ASE.

The post Modernize your database with the consolidation and retirement of Azure Database Migration tools appeared first on Microsoft SQL Server Blog.

“With our migration to PaaS, we got what we wanted: greater scalability, reliability, security, agility in managing our IT infrastructure—and greater peace of mind—all without the cost and hassle of doing this ourselves,” 

Daniel Engberg, Head of AI, Data, and Platforms at Scandinavian Airlines System  

Migrate to Microsoft Azure

Boost productivity and enable innovation.

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This blog post will guide you through several best practices our customers employed when faced with the SQL Server end-of-support moment. Customers have three choices for handling their out-of-support SQL Server workloads: moving or updating to Azure, upgrading to SQL Server 2022, or getting Extended Security Updates (ESUs) for additional preparation time. 

Migrate and modernize to Azure, a smooth path, a more powerful destination 

Migrating to a cloud platform is an essential step on the journey to modernization, and there are many choices. What makes SQL Server and Microsoft Azure SQL unique is that it’s built on the same engine, no matter where you deploy, which means you can build on your existing SQL experience while gaining the layered security, intelligent threat detection, and data encryption that Azure provides. 

Modernizing to Microsoft Azure SQL Managed Instance offers cost savings, scalability, security, seamless migration, productivity, and always up-to-date features. Some of the recent product highlights include Azure SQL Managed Instance Next-gen General Purpose, now in public preview, which supports twice as many Azure VMs configurations, making migration and modernization faster and easier than ever before for a larger number of customer scenarios. Customers can experience the full capabilities of managed SQL Server in the cloud at no cost for the initial 12 months with access to a General Purpose instance capable of accommodating up to 100 databases, along with 720 vCore hours of compute per month (non-accumulative) and 64 GB of storage through Azure SQL Managed Instance Free Tier, now in public preview. 

Modernizing your SQL Server workloads to Azure also presents a chance to utilize cutting-edge innovation like Microsoft Copilot. Microsoft Copilot in Azure has extended its capabilities to Microsoft Azure SQL Database with new skills designed to enhance the management and operation of SQL-based applications.  

Extending end-of-support time

If you are ready to move to the cloud but feel challenged to upgrade or modernize before the end of the support timeline, Extended Security Updates are available for free in Azure for SQL Server 2014 and 2012 and Windows Server 2012. Secure your workloads for up to three more years after the end of the support deadline by migrating applications and SQL Server databases to Microsoft Azure Virtual Machines. Free Extended Security Updates are available for Azure Virtual Machines including Microsoft Azure Dedicated Host, Microsoft Azure VMWare Solution, Nutanix Cloud Clusters on Azure, and Microsoft Azure Stack (Microsoft Azure Stack Hub, Microsoft Azure Stack Edge, and Microsoft Azure Stack HCI). Combining Extended Security Updates in Azure with Azure Hybrid Benefit further reduces your costs. With these pricing advantages, AWS is up to five times more expensive than Azure for SQL Server and Windows Server end-of-support workloads. 

In-place upgrade to SQL Server 2022 

Another way to stay protected is to upgrade your SQL Server to SQL Server 2022, the most Azure-enabled release yet. Get more out of your data with enhanced security, industry-leading performance and availability, and business continuity through Azure. 

SQL Server 2022 is the most Azure-enabled release of SQL Server, with continued innovation across performance, security, and availability. Gain deeper insights, predictions, and governance from your data at scale. Take advantage of enhanced performance and scalability with built-in query intelligence. 

Stay protected on-premises or in multi-cloud environments with Azure Arc 

Just as with SQL Server 2012, Extended Security Updates for SQL Server 2014 offers an enhanced cloud experience through Microsoft Azure Arc. First year coverage from Extended Security Updates started on July 10, 2024. With this more customer-centric approach, security updates will be natively available in the Microsoft Azure portal through Azure Arc. This also provides Azure benefits and flexible subscription billing for SQL Server 2014 workloads on-premises or in multi-cloud environments. 

We’re continuing to enhance the capabilities Azure Arc offers to Extended Security Updates. Just recently, physical-core licensing with unlimited virtualization was released for SQL Server 2012 and 2014 ESUs. For customers who need to maximize database performance or require security isolation and better resource management, physical core licensing provides a more cost-effective way to leverage Extended Security Updates via Azure Arc. 

Also, if you enabled ESU subscription in your production environment managed through Azure Arc, you can enable SQL Server ESU subscription in the non-production environment for free, through SQL Server Developer Edition or an Azure dev/test subscription. 

We encourage all our customers running SQL Server 2014, Windows Server 2012, and Windows Server 2012 R2 to start planning for the end of support. We have migration resources, best practices, and more, as well as a rich ecosystem of partners ready to help. To get started, please visit the following pages to learn more. 

Learn More 

• Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers 
• Get the full ROI and TCO reports from IDC: The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload and The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads 
• Previous announcement on SQL Server 2014 End-of-Support moment: Protect SQL Server 2014 workloads with Azure flexibility – Microsoft SQL Server Blog

The post Modernize Microsoft SQL Server 2014 workloads with Azure appeared first on Microsoft SQL Server Blog.

During recent years, Azure has undergone significant evolution, marked by groundbreaking innovations like Microsoft Fabric and Azure Data Lake Storage. As we continue this journey, it remains imperative to keep evolving our approach on hybrid data storage, ensuring optimal empowerment for our SQL Server customers in leveraging the best from Azure.

Retirement of SQL Server Stretch Database 

On November 16, 2022, the SQL Server Stretch Database feature was deprecated from SQL Server 2022. For in-market versions of SQL Server 2019 and 2017, we had added an improvement that allowed the Stretch Database feature to stretch a table to an Azure SQL Database. Effective July 9, 2024, the supporting Azure service, known as SQL Server Stretch Database edition, is retired. Impacted versions of SQL Server include SQL Server 2022, 2019, 2017, and 2016.  

In July 2024, SQL Server Stretch Database will be discontinued for SQL Server 2022, 2019, 2017, and 2016. We understand that retiring an Azure service may impact your current workload and use of Stretch Database. Therefore, we kindly request that you either migrate to Azure or bring their data back from Azure to your on-premises version of SQL Server. Additionally, if you’re exploring alternatives for archiving data to cold and warm storage in the cloud, we’ve introduced significant new capabilities in SQL Server 2022, leveraging its data virtualization suite. 

The path forward 

SQL Server 2022 supports a concept named CREATE EXTERNAL TABLE AS SELECT (CETaS). It can help customers archive and store cold data to Azure Storage. The data will be stored in an open source file format named Parquet. It operates well with complex data in large volumes. With its performant data compression, it turns out to be one of the most cost-effective data storage solutions. Using OneLake shortcuts, customers then can leverage Microsoft Fabric to realize cloud-scale analytics on archived data.  

Our priority is to empower our SQL Server customers with the tools and services that leverage the latest and greatest from Azure. If you need assistance in exploring how Microsoft can best empower your hybrid data archiving needs, please contact us.

New solution FAQs

What’s CETaS? 

Creates an external table and then exports, in parallel, the results of a Transact-SQL SELECT statement. 

• Azure Synapse Analytics and Analytics Platform System support Hadoop or Azure Blob Storage.
• SQL Server 2022 (16.x) and later versions support CETaS to create an external table and then export, in parallel, the result of a Transact-SQL SELECT statement to Azure Data Lake Storage Gen2, Azure Storage Account v2, and S3-compatible object storage. 

What is Fabric? 

Fabric is an end-to-end analytics and data platform designed for enterprises that require a unified solution. It encompasses data movement, processing, ingestion, transformation, real-time event routing, and report building. Fabric offers a comprehensive suite of services including Data engineering, Data Factory, Data Science, Real-Time Analytics, Data Warehouse, and Databases. 

With Fabric, you don’t need to assemble different services from multiple vendors. Instead, it offers a seamlessly integrated, user-friendly platform that simplifies your analytics requirements. Operating on a software as a service (SaaS) model, Fabric brings simplicity and integration to your solutions. 

Fabric integrates separate components into a cohesive stack. Instead of relying on different databases or data warehouses, you can centralize data storage with Microsoft OneLake. AI capabilities are seamlessly embedded within Fabric, eliminating the need for manual integration. With Fabric, you can easily transition your raw data into actionable insights for business users. 

What is OneLake shortcuts?  

Shortcuts in OneLake allow you to unify your data across domains, clouds, and accounts by creating a single virtual data lake for your entire enterprise. All Fabric experiences and analytical engines can directly connect to your existing data sources such as Azure, Amazon Web Services (AWS), and OneLake through a unified namespace. OneLake manages all permissions and credentials, so you don’t need to separately configure each Fabric workload to connect to each data source. Additionally, you can use shortcuts to eliminate edge copies of data and reduce process latency associated with data copies and staging. 

Shortcuts are objects in OneLake that point to other storage locations. The location can be internal or external to OneLake. The location that a shortcut points to is known as the target path of the shortcut. The location where the shortcut appears is known as the shortcut path. Shortcuts appear as folders in OneLake and any workload or service that has access to OneLake can use them. Shortcuts behave like symbolic links. They’re an independent object from the target. If you delete a shortcut, the target remains unaffected. If you move, rename, or delete a target path, the shortcut can break. 

Learn more 

• Stretch Database
• Deprecated database engine features in SQL Server 2022
• Install an on-premises data gateway
• SQL Server in Microsoft Fabric? Use CETaS to move data!
• OneLake shortcuts
• CREATE EXTERNAL TABLE AS SELECT (CETaS)

Microsoft Fabric

Bring your data into the era of AI

Explore solutions

The post Announcing the retirement of SQL Server Stretch Database appeared first on Microsoft SQL Server Blog.

Azure SQL and SQL Server support building new generative AI experiences that become supercharged when combined with your data. In addition, SQL brings AI assistance to a new level with copilot experiences for both self-help and natural language to SQL capabilities.

In this blog post, I’ll share how you can get started with these new AI experiences—Azure SQL and SQL Server. First, check out our latest story on Microsoft Mechanics:

Responsible AI

Many conversations about AI starts with a statement on responsible AI. Microsoft has established a set of policies, research, engineering efforts, and principles to ensure AI technologies are adopted, implemented, and used in a responsible manner.

These principles include fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Your data is your data. One promise for Microsoft is that private data of any user, including prompts and responses, are never used to fine tune a model that Microsoft hosts or implements.

Generative AI applications with your data

One of the motivations for generative AI applications is to become more productive, creative, and efficient through the generation of content in all forms: text, audio, and video. Many of today’s examples for generative AI applications involve the user of a natural language prompt and the interaction with a language model. Many of you have probably at some point used an application like ChatGPT or Microsoft Copilot which are great examples of generative AI applications.

Get smarter with your data

While these are great applications, they don’t know about your data. The combination of a generative AI application with your data, for example, stored in a database, can be quite powerful. Generative AI provides methods for smarter searching on your data. A common application pattern is to use language models with a prompt application to “chat with your data.” Using the concept of vector embeddings, language models allow you to get more precision on questions about your data. In addition, responses to questions are more tailored to your users and searches can often be faster because language models allow you to use the power of natural language. Generative AI applications with your data provide unique intelligence in an interactive manner, including conversations. Language models are trained to provide more context on your search, often giving you more (hence generated) content than you might normally get using common searching techniques within a database engine with a language like SQL.

Prompt engineering, Retrieval Augmented Generation fundamentals, and hybrid search

As you investigate how you can take advantage of generative AI with language models, there are two important concepts to understand:

Prompt engineering is the discipline of using high quality and descriptive prompts when interacting with a language model. The concept is simple. The better the prompt, the likelihood of a better response from the model. For example, let’s say you use Microsoft Copilot and type in a prompt like “What are the best steak restaurants in Fort Worth, Texas?” You will get a good list of steak houses in Fort Worth, Texas based on a search by Copilot of rankings across a broad set of searches. But what if you are on a bit of a tight budget? Instead of looking at the results from the prompt and trying to figure out what prices you can afford you could instead ask “I’m on a tight budget but want to eat at a good steakhouse in Fort Worth, Texas.” Now your results are more tailored for what you really want. And since you are interacting with a language model, it understands the phrase “tight budget” means you need choices that are good but affordable.

While this technique can be great if you are interacting with a model that is trained to help you search the internet, what about your own data? One prompt engineering technique to get smarter with your data is called Retrieval Augmented Generation (RAG). The concept of RAG is to search for information from a source of data and use those results to augment the prompt to the model. For Azure SQL and SQL Server, this could mean using standard SQL techniques to search for data using Transact-SQL (T-SQL), taking these results, and sending them along with the original prompt to the language model. This technique is simple and can be an effective way to get smarter with your data, and this can work with almost any type of data you search, not just SQL databases.

For Azure SQL and SQL Server, a more sophisticated technique is called hybrid search. With hybrid search, you can use the power of vector search combined with the query capabilities of your SQL data. Vector embeddings are numerical representations of data that capture semantic meaning and similarities. The key to embeddings with language models is that the model can generate embeddings based on data like text. This means you can take text data inside your SQL database and use a model to generate embeddings and then store these embeddings in your database. Now anytime you want to search for data inside the database, you can send a prompt to a language model which will generate embeddings for the prompt. And then you can use vector search techniques to compare the embeddings from the prompt with the embeddings stored in your database. You can then combine the vector search with other techniques you would normally use in T-SQL to find data in your database: a hybrid search.

There are methods today to use hybrid search completely inside the engine using T-SQL and outside the engine using Microsoft Azure AI Services or frameworks like LangChain or Semantic Kernel.

Get started quickly with Azure AI Services

One approach to get started quickly with no code required is to index your SQL database using Azure AI Search and then use Azure OpenAI Service to build a simple prompt app and “chat with your data” using a hybrid search technique.

You can use Azure AI Search to build an index based on a table in your SQL Server or Azure SQL database. When you build the index, you can apply a skillset to generate embeddings based on your data and store the result in the index. Now you can use Azure OpenAI with a prompt application to perform hybrid searches on your data. One example prompt application to perform simple testing is to use Azure AI Studio. In addition, as you change your SQL data, the index is automatically updated including the embeddings. The figure below shows the basic flow:

You can see this in action from the latest Microsoft Mechanics video or download a deck with demo recordings. One of the interesting aspects of this example is the method of changing the system message to direct the language model to respond in a unique way using the same data. This is also a great example of prompt engineering.

Learn more about Azure SQL in Azure AI Search.

Use hybrid search inside the engine with T-SQL

Let’s say instead of using a separate index, you would like to build generative AI capabilities for your application all inside the engine using T-SQL. You can do this in a very powerful way for Azure SQL Database today using a combination of vector embeddings, vector search, and other T-SQL search methods. This is a true hybrid search because you are using all the power of the SQL query processor together with a vector search. An example my colleague Davide Mauri has developed uses these techniques to help him find the best restaurant for one of this favorite Italian foods, focaccia bread.

Davide built an application that stores reviews from restaurants in the form of vector embeddings using Azure OpenAI Service with Azure SQL Database Representational State Transfer (REST) API inside the engine. With this in place, he can take any prompt to search for the best focaccia bread and use the same technique to generate embeddings for the prompt. Then, he can use a new T-SQL vector_distance function to perform a similarity search. The true power of SQL is possible because Davide built queries to combine this vector search with other criteria from spatial types, the new JSON data type, and the new Regular Expression (RegEx) T-SQL capabilities.

You can see a diagram of how these techniques are combined together below:

You can see this demo in action in our Microsoft Mechanics video or download a deck with demo recordings. You can learn more about the new JSON data type (preview). You can also sign-up to preview the new vector search capabilities and RegEx in Azure SQL Database.

Building generative AI applications using frameworks

There are other methods to build generative AI applications with Azure SQL and SQL Server using frameworks such as:

• LangChain:
  LangChain is an open-source framework to orchestrate AI applications with language models. You can use programming languages such as Python and JavaScript to build your own generative AI application. LangChain supports the SQL Agent Toolkit which allows you to interact with a SQL database using natural language prompts. The toolkit integrates the connection to your database with a language model to generate SQL queries based on natural language prompts. You can see an example of this in the blog post “Building your own DB Copilot for Azure SQL with Azure OpenAI GPT-4.”
• Semantic Kernel:
  Semantic Kernel is an open-source SDK to allow you to build AI applications in C#, Python, and Java, interfacing with many common models in the industry such as OpenAI, Azure OpenAI, and Hugging Face. A library has been built to allow a Semantic Kernel application to interact with Azure SQL Database (and use the new vector search capability) called the SQL Connector.

See a full range of SQL and generative AI examples.

The age of copilots

Microsoft has transformed the industry and how we work and live with a new set of AI assisted experiences called Microsoft Copilot. Copilots are AI companions that work everywhere you do and intelligently adapt to your needs.

Use Copilots where you live

I realize there seem to be copilots everywhere. It is hard to keep track. Microsoft is investing in Copilot experiences in almost every product or service. Use the product or service you normally do and see what Copilot can offer. For example, if you have Microsoft 365, use Copilot for Microsoft 365 naturally within Microsoft Teams or any Office product or service. I personally use Microsoft Copilot in my Edge browser or on the app on my phone for any search experience I need today—web or work related.

Microsoft Copilot in Azure

The primary resource to manage and explore Microsoft Azure is the Azure portal. You can now use Microsoft Copilot in Azure within the Azure portal to manage, deploy, and troubleshoot Azure resources. Azure SQL Database is one of the most popular Azure resources in the world, so we have built two distinct experiences within the Copilot in Azure framework using natural language for self-guided assistance and T-SQL query authoring:

Microsoft Copilot in Azure integration

One of the strengths of SQL Server is the deep built-in telemetry within the engine all accessible through T-SQL. This includes Dynamic Management Views (DMV) and Query Store. These rich, traditional capabilities shine through now in Copilot. For example, you can prompt with Copilot a general statement like “My database is slow” and Copilot, based on your permissions, will access real-time diagnostic data, in the context of your database, to help you quickly navigate difficult, and often vague, performance problems. Here is an example:

You can then continue a conversation with Copilot to tune the query causing the problem. There are many different skills that Copilot can help you all in the context of your database. Learn about all the possibilities of Copilot skills in Azure SQL Database (preview).

Natural language to SQL

The T-SQL query language has so many great capabilities and possibilities. But the open nature of T-SQL also leads to difficulties in crafting queries to meet the need of your application. Along comes a copilot experience to allow you to “chat” with your database using natural language in the context of your database and schema: table, columns, and key relationships. A simple example is being able use a natural language statement to generate a query that typically requires several joins over multiple tables like the following:

Learn more how to use natural language to SQL.

You can see both experiences in action in our Microsoft Mechanics video or download a deck with demo recordings.

Innovations moving forward

We are just beginning with SQL and AI. We have innovations for the future planned for enhancements with AI services, enhancements for deep integration for vector search, and enhanced Copilot experiences for SQL Server. Stay tuned for future blog posts showing all of these innovations.

Learn more today

Here are more resources for you to learn more about SQL and AI:

• Explore the capabilities of Azure SQL Database.
• Keep track of SQL and AI at our one-stop documentation hub.
• Keep track of all of our SQL and AI examples.
• Showcase your own demos using our decks with demo recordings built-in.
• Read our team’s blog on developer experiences for SQL including the latest AI examples at Azure SQL Devs’ Corner.
• To see all this in action, check out our new Microsoft Mechanics video.
• Learn the essentials to building a SQL generative AI application.
• Check out the comprehensive blog post from Sanjay Mishra to explore the power of generative AI applications with Azure SQL Database.
• Learn more about Copilot in Azure SQL Database experiences from Joe Sack’s Data Exposed episode.
• Check out our Microsoft Build 2024 sessions:
  • Power AI apps and develop rich experiences with Azure SQL Database
  • The power of AI and Copilot for Azure Databases

Azure SQL

Migrate, modernize, and innovate with the modern SQL family of cloud database services

Start your journey

The post Getting started with delivering generative AI capabilities in SQL Server and Azure SQL appeared first on Microsoft SQL Server Blog.

We’ve been on the road the last couple of weeks at MVP Summit, SQLBits and Fabric Con, connecting with customers talking about the value of migration and modernization. We want to dig into specifically, how Azure can deliver real business value through cost optimization and streamlined productivity for their Windows Server and SQL Server deployments when they migrate to Azure. 

We’ve helped countless organizations migrate their SQL Server and Windows workloads to Azure a critical 1^st step in any transformation initiative. The move can help improve cybersecurity posture and business continuity, boost productivity, and lay the foundation for AI and other highly scalable data innovations, while automating updates, backups, and other time-consuming IT tasks. 

Modernize and lower total cost of ownership (TCO) 

Migration is a business strategy that pays off. In The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload,¹ organizations that migrated to Azure SQL Managed Instance and Microsoft Azure SQL Database can get up to 406 percent return on investment over 3 years and can expect a 30-percent reduction in TCO over 5 years, protecting an additional $6.85 million in annual revenue.

A separate study found that customers that migrated both Windows Server and SQL Server workloads to Azure generated more value. According to The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads,² by optimizing costs, operations, and business opportunities, companies gained $15.85 million in total annual benefits while also increasing IT security efficiency by 43 percent with cloud tools and automation.

Azure SQL

Migrate, modernize, and innovate with the modern SQL family of cloud database services.

Start today

A smooth path to migration, a more powerful destination

Migrating to a cloud platform is an essential step on the journey to modernization, and there are many choices. 

What makes SQL unique is that it’s built on the same engine, no matter where you deploy, which means you can build on your existing SQL experience while gaining the layered security, intelligent threat detection, and data encryption that Azure provides. And as we shared with customers at SQLBits, there’s now an even more powerful option available for customers looking to leverage the full PaaS experience. Azure SQL Managed Instance Next-gen GP  brings significantly improved performance and scalability to power up your existing Azure SQL Managed Instance fleet, and help bring more mission-critical SQL workloads to Azure. With close to 100 percent feature compatibility with SQL Server, Azure SQL Managed Instance is the recommended choice to migrate and modernize SQL apps at scale and at your own pace.

Another option many of our customers start with is by running their Windows Server workloads on Azure Virtual Machines, benefiting from a simplified, managed experience and cloud-native support for SQL Server, .NET apps, and Remote Desktop Services. Or you can modernize your entire Windows Server estate, choosing from more than 200 Azure services and capabilities, including support for hybrid environments. 

Take the first step or the next: You have choices

When it comes to migration, Azure meets you where you are with options for moving on-premises workloads and for developing new cloud solutions. For example, many organizations start by moving Windows Server workloads to Azure Virtual Machines, enabling them to easily scale to support new developments and more efficiently manage peak loads. Hokkoku Bank took this step, migrating its Windows Server–based estate to Azure as part of a cloud-first initiative. Azure supports the bank’s modernization plans and helps provide a disaster recovery solution in an earthquake-prone region.  

Correios de Portugal, the country’s postal service, migrated its Windows Server workloads to Azure Virtual Machines backed by Azure SQL, which provides a smooth path to a cost-effective, highly scalable, fully managed PaaS database. It’s the best choice for modernizing your apps and getting the most out of your existing investments.

Many of our database customers move to SQL Server on Azure Virtual Machines for the cost benefits on top of the scalability and resilience of Azure. As an example, healthcare software manufacturer Allscripts migrated on-premises applications to Azure SQL Database Managed Instance when possible, but another 600 on-premises VMs needed a different migration approach. Allscripts moved them to SQL Server on Azure Virtual Machines, a quick, low-risk step for workloads it plans to optimize and modernize later. The lift-and-shift approach can be an easy first   step in your cloud journey.

Azure also offers hybrid solutions that bridge your on-premises and cloud resources. For example, you can move or extend on-premises VMware environments using Azure VMWare Solution. You can even use the free Windows Admin Center tool to manage across Windows Server environments—physical, virtual, on-premises, in Azure, or in a hosted environment—at no additional cost. To get started with a Windows Server migration, start discovering and assessing on-premises resources using the free Azure Migrate tool.

Watch the Migrate to Innovate digital event on demand and learn the business benefits of migrating to Azure.

Try it for free 

If you want to know how your workload will perform before migrating, try these Azure offers and get started building that proof-of-concept.  

• Try Azure SQL Managed Instance for free. For 12 months, you can get up to two instances per Azure subscription, 750 vCore hours of compute per month, and 32 GB data storage and 32 GB backup storage per month. 

• Try Azure SQL Database for free. Test and develop applications or run small production workloads for free. This offer provides the first 100,000 vCore seconds, 32 GB of data, and 32 GB of backup storage per month at no charge for the lifetime of your subscription. 

• Try Windows Server in the cloud with an Azure free account. Extend your existing Windows Server datacenter and try out popular services free for 12 months. 

Learn more about Azure SQL

Stay tuned for more migration announcements in the coming months. To get started now: 

• Get the full ROI and TCO reports from IDC: The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workload and The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads.

• Review the benefits of migration in Better on Azure: The benefits of using Azure for Windows Server and SQL Server workloads. 

• Discover why cloud economics make sense and get greater return on your investment. 

1. IDC report, The Business Value of Microsoft Azure SQL Database and Azure SQL Managed Instance Workloads, IDC #US51073123, August 2023. 
2. The Business Value of Microsoft Azure for SQL Server and Windows Server Workloads

The post Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers appeared first on Microsoft SQL Server Blog.

This week, we are proud to be back in front of our community at SQLBits, together with our partner AMD to share the latest innovations from ground to cloud and beyond. From SQL Server, Azure SQL, to our powerful solutions like Microsoft Fabric and Microsoft Copilot, these product enhancements are designed to help make application migration, modernization, and development easier so you can power what’s next.

Better performance with the next generation of Azure SQL Managed Instance ​ 

What sets the SQL Server family apart from other operational databases is that it’s all built on the same SQL engine. So, whether you’re running at the edge or in the cloud, the power to unlock the potential of data and AI is always there. We’re announcing the public preview of Azure SQL Managed Instance Next-gen GP, now even more powerful and performant. Accelerate your migrations and efficiently manage your unique workload demands. Enhance your productivity with superior performance and adaptable compute and storage choices. Join the preview to maximize your efficiency.  

We now have a way customers can get stated with Azure SQL Managed Instance. Our free offer gives you:

• A General Purpose instance with up to 100 databases
• 720 vCore hours of compute every month
• 64 GB of storage

Azure SQL Managed Instance

Enhance your productivity with superior performance and more

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AI-power your Azure SQL Database experience with Copilot 

We are bringing the power of Copilot to Azure SQL Database, now in private preview. Copilot in Azure SQL Databases delivers a set of AI-enhanced experiences built to help streamline design, operation, optimization of Azure SQL Database-driven applications, and improve productivity in the Azure Portal. This new functionality introduces two new Azure portal experiences: 

• Natural language to SQL: This experience within the Azure portal query editor for Azure SQL Database translates natural language queries into SQL, making database interactions more intuitive.  
• Microsoft Copilot for Azure integration: This experience adds Azure SQL Database skills into Copilot for Azure, customers with self-guided assistance, empowering them to manage their databases and solve issues independently.  

Sign up for the preview access.

Simplify your journey to Azure with SQL Server enabled by Azure Arc 

Earlier this month, we introduced a way to streamline migration to Azure SQL with SQL Server enabled by Azure Arc. Migration assessment removes some of the complexity around cloud migration by helping you better assess your SQL Server readiness for Azure SQL. Through the Azure Arc agent, customers can get help with:

• Streamlining discovery and migration readiness assessments.
• Evaluating and measuring the readiness of SQL Server instance and databases.
• Getting best-fit recommendations.   

Learn about this assessment “SQL Server enabled by Azure Arc, now assists in selecting the best Azure SQL target.” 

Deliver better value and power AI with Flexible Server in Azure Database for PostgreSQL 

In November 2023, we announced the preview of the new Azure AI extension, enabling you to integrate Azure AI services with your operational data in Azure Database for PostgreSQL. Now, we’re sharing that Flexible Server in Azure Database for PostgreSQL is now directly integrated with Azure OpenAI Service. Learn how to use Azure AI with Azure Database for PostgreSQL.

We were excited to have our AMD partners join us to co-sponsor SQLBits to showcase how best in class technology partnerships can help customers achieve their business outcomes for both SQL Server and PostgreSQL workloads. A recently commissioned Principled Technologies report found that for customers who migrated to Azure Databases for PostgreSQL—flexible server, backed by AMD EPYC™ processors—saw significantly faster online transaction processing (OLTP) performance, in fact, 4.71 times new orders per minute when compared to single server. Customers also achieved better value, 3.88 times the performance per dollar. Read the full report.

We look forward to the week ahead and connecting with you in person. 

The post Expand the limits of innovation with Azure data appeared first on Microsoft SQL Server Blog.

We are excited to get back in front of customers at Microsoft Ignite 2023 and PASS Data Community Summit to announce powerful product enhancements across Microsoft Azure databases designed to help customers take the next step or the first step in their transformation journey, with databases that are intelligent, trusted, and ready for developers to build, without limits.   

Limitless innovation for cloud native applications

If you are an application developer looking for a flexible relational cloud database solution with performance and scalability to support your most demanding applications, you’ll want to check out Microsoft Azure SQL Database Hyperscale. Built on a unique architecture that splits the storage and compute nodes, these resources scale independently to meet the unique requirements of your apps. Plus, you can eliminate the need to pre-provision storage resources, as the storage automatically scales to meet demand, with support of up to 100 TB. We are thrilled to announce that we are introducing lower compute pricing on SQL Database Hyperscale, saving customers up to 35 percent on their compute bill. Effective December 15, 2023, customers will have competitive pricing on the resources they need to build scalable, secure, AI-ready applications. 

We’re also excited to share that the Microsoft Azure SQL Managed Instance feature wave has reached general availability. This set of features improves Azure SQL Managed Instance’s performance, reliability, and security. The latest release will deliver deeper integration with Microsoft SQL Server on-premises and the wider Azure service platform. And soon, customers will be able to start testing Azure SQL Managed Instance for free. Landing in December 2023, customers will be able to run proof of concepts, test applications or simply learn more about the operational benefits of a fully managed database-as-a-service. This is in addition to the free Azure SQL Database offer that launched in October 2023.  

Microsoft is also excited to share the newest updates for our fully managed community based open-source databases. These services help you manage your database and database infrastructure with automation, freeing you from the routine database management tasks so you can concentrate on what matters most.

Enhanced performance and scalability for Microsoft Azure Database for PostgreSQL

The latest enhancements for Azure Database for PostgreSQL deliver advanced storage and compute capabilities that enable optimal price-performance for enterprise production workloads. Customers can expect enhancements for advanced storage, compute capabilities, and flexibility for managing performance and cost.  

Azure Database for PostgreSQL extension for Azure AI

The PostgreSQL extension for Azure AI allows developers to use large language models (LLMs) and build rich PostgreSQL generative AI applications, meaning PostgreSQL queries on Azure can now power Azure AI applications. It enables calling into Microsoft Azure OpenAI Service to generate LLM-based vector embeddings that allow efficient similarity searches, which is particularly powerful for recommendation systems, as well as calling into Azure AI Language for a wide range of scenarios such as sentiment analysis, language detection, entity recognition, and more.

New performance enhancements in Microsoft Azure Database for MySQL Business Critical 

New performance enhancements in Azure Database for MySQL Business Critical service tier makes it ideal for high-performance transactional or analytical applications. In fact, a recent performance benchmark study by Principled Technologies shows that Azure Database for MySQL Business Critical service tier is up to 50 percent faster than MySQL on Amazon Web Services Relational Data Service and up to 2.26 times faster than Google Cloud Platform Cloud SQL for MySQL. These key innovations help make Azure Database for MySQL Business Critical the perfect option to run mission-critical, Tier 1 MySQL workloads.

Extend Azure to your entire data estate

For all the innovation that customers are driving in the cloud, we recognize much of the customer’s data remains on-premises. This is why Microsoft continues to invest heavily in ensuring that customers can get the most from their entire data estate with Microsoft Azure Arc. The latest monitoring capabilities from SQL Server-enabled by Azure Arc are designed to deliver critical insights across your entire SQL Server environments, optimizing database performance and delivering fast diagnostic times.  

Customers can also now improve SQL Server business continuity and consistency by viewing and managing Always On availability groups, failover cluster instances, and backups directly from the Azure portal. This capability provides better visibility and an easier, more flexible way to configure critical database operations.  

In addition, with Extended Security Updates as a service and automated patching, customers can always keep their apps secure, compliant, and up to date. Learn more about these latest features.

We look forward to the week ahead and connecting with you in person.

The post Power what’s next with limitless relational databases from Azure appeared first on Microsoft SQL Server Blog.

Azure Data Studio

A modern open-source, cross-platform hybrid data analytics tool designed to simplify the data landscape.

Learn more

Connectivity

The migration from the Active Directory Authentication Library (ADAL) to Microsoft Authentication Library (MSAL) was a significant undertaking by the team. This was necessary as ADAL support ends in June of this year, and it provides multiple benefits for those environments using Azure Activity Directory (AAD). AAD users should notice an improved and more reliable experience, particularly around token refresh and connection stability. This also helped us fix an issue in the MySQL extension for AAD. 

Additional changes include improved loading of Azure resources and new Dedicated SQL Pools and Azure Synapse Analytics nodes in the Azure tree. Azure Data Studio 1.41 also provides the ability to customize the name of firewall rules for Azure SQL and adds support for connecting to a server alias (versus a server name).

If you have applications that use ADAL, please see the Migrate applications to the Microsoft Authentication Library (MSAL) page for more information.

Object explorer

A new area of focus in this release is Object Explorer (OE), and this will continue to be an area we improve upon in the next few releases. Those with serverless Azure SQL previously reported issues with folders not expanding correctly, and with databases being brought online (thus incurring costs) when it was not expected. Other users noted that expanding OE timed out after 45 seconds. We have addressed all these issues in this release, in addition to adding support for Ledger Views.

Query results

The query results window got a fair bit of attention this release as we work through the backlog of open issues. First, we introduced a new configuration option to show or hide the action bar in the query results view. The Query Editor > Results: Show Action Bar option can be found in the command palette (CTRL + , ) if you type Show Action Bar. By default, the action bar is shown in the query results pane, as seen in the screenshot below:

There are also improvements around opening JSON files and the visibility of the horizontal scroll bar in the query results pane. Azure Data Studio 1.41 now correctly handles line breaks in cells when copying from the results grid and pasting to an editor, and the auto-resizing of columns in the output pane has been updated to better display column contents. Finally, cell selection and navigation in the results grid have been enhanced, and we introduced additional summary details when selecting multiple cells in the results window:

Extensions

Multiple teams have been working on updates to various extensions available from Azure Data Studio.  For SQL Projects, we have improved the experience of finding projects by providing a dropdown that lists saved projects, rather than requiring users to browse to their location. We had reports that differences in schema compare were not highlighted correctly, and that problem has been fixed.

Users of the SQL Migration extension will see an improvement in the migration process as we better support migrations to specific subscriptions (such as government), and the extension now includes the Premium Series Memory Optimized SQL MI SKU as a recommendation where appropriate.

MongoDB and Microsoft Azure continue to build on their partnership by introducing an extension for MongoDB Atlas and Azure Data Studio on the Azure Marketplace. This Extension is available in Public Preview as of today, Wednesday, January 25, 2023.  You already know that Azure Data Studio is a modern open-source, cross-platform hybrid data analytics tool designed to simplify your data landscape, and customers can use Azure Data Studio to work with their data sitting in one or more Azure data services. MongoDB Atlas on Azure provides a fully managed solution for MongoDB in the cloud, and you can now seamlessly connect to and query data on MongoDB Atlas right from Azure Data Studio. This allows you to interact with data on MongoDB Atlas alongside other data services and provides a unified view of your data estate.  If you are an Azure customer that is curious about building applications with MongoDB Atlas and want to amplify your integrated experience inside Azure Data Studio, try Pay-As-You-Go Atlas on the Azure Marketplace today!

With this 1.41 release, the Polyglot Notebooks extension will be removed from the Azure Data Studio Extension Marketplace. For a polyglot notebooks experience, we recommend folks use the Polyglot Notebooks in Visual Studio Code.

Odds and ends

Continuing on our path of adding support for arm64, we now include support for arm64 on Windows.  Whether you run iOS or Windows, Azure Data Studio 1.41 now provides the capability to leverage arm64, resulting in improved performance.

We are pleased to see users embracing Table Designer and Query Plan Viewer, two features that became generally available (GA) in the November release. In 1.41 we fixed an issue related to opening Table Designer for Ledger tables, and one related to creating a table when another table with the same name already exists.

There were also two requests specific to Query Plan Viewer that got attention in this release. When saving query plan files from Azure Data Studio, we now incrementally append a number to the end of the file for unique naming, and we’ve altered the default folder location when saving plans for a more consistent experience.

Lastly, we had previously announced that we were removing Big Data Cluster functionality from Azure Data Studio. This removal has been delayed until a later release.

Looking forward

We are already at work on the next release of Azure Data Studio and are making plans for what we want to accomplish in 2023. You can expect that we will continue to review backlog issues and address them as they relate to an existing area of focus. We have more changes coming related to the connection dialog and object explorer, and you will also see improvements in user management. Finally, if you see a comment on an issue you opened–whether recent or ages ago–please feel free to respond and provide more information if you are able. 

The post Azure Data Studio 1.41 release appeared first on Microsoft SQL Server Blog.

In addition to these two features now being generally available, we are pleased to announce enhancements in the assessment tooling for Oracle database migration to Azure Database for PostgreSQL and Azure SQL, both in preview. The MySQL extension for Azure Data Studio is also available in preview, as is Azure SQL Database Offline Migration support in the Azure SQL Migration extension. We would also like to introduce arm64 macOS support, for which many of you have been patiently waiting for (more details below).

As you may already know, SQL Server 2022 is generally available today, and we have introduced support for this latest version of SQL Server via our deployment wizard. We have made improvements to the connection experience, including a change to the Encrypt property, which now defaults to True. Finally, we completed another set of Visual Studio (VS) Code merges that included numerous bug fixes and UI improvements, some of which are highlighted below.

arm64 macOS support in Azure Data Studio

Over one year ago we had a request to add support to Azure Data Studio for arm64 on macOS. We are pleased to announce that in this release, said functionality is now available. Folks using arm64 macOS will notice that the Azure Data Studio builds for Apple Silicon or Universal will load and run significantly faster as emulation is no longer needed. There are a few extensions that still need to be modified to have the same support and we are working with the appropriate teams to get those changes in place. Interested in seeing support for arm64 on Windows? Share your comments and upvote here.

Change in default value for Encrypt Property

Version 1.40 of Azure Data Studio includes an important change to the Encrypt property for the MSSQL provider connections, which is now enabled by default (set to True). 

In Azure Data Studio 1.39 and below, the Encrypt connection property was on the Advanced page and defaulted to False. As shown below, both the Encrypt and Trust server certificates have been moved to the main Connection Details for Microsoft SQL Server connections, with information icons to provide more detail on hover.

The Encrypt property continues to support two options:

1. True (now the default value)
2. False

Upon upgrading to Azure Data Studio 1.40, users should review the options selected for Encrypt and Trust server certificate before connecting. More information about this change can be found here.

Introducing assessment tooling for Oracle database migrations to Azure Database for PostgreSQL and Azure SQL (preview)

Enabling the migration of Oracle workloads to Azure PostgreSQL and Azure SQL through a unified assessment tool has been a key ask from customers and we are excited to announce the preview release of this experience in Azure Data Studio via the Database Migration Assessment for Oracle extension (check out this demo to see this in action). With these changes, migration planning is simplified for customers looking to modernize their data estate to Azure managed databases. This new assessment scenario helps customers speed up migrations while reducing risk, making it easier than ever to move Oracle databases to Azure. Read more in this blog announcement.

MySQL extension is now available in Azure Data Studio (preview)

As you may have heard at Microsoft Ignite, the MySQL extension for Azure Data Studio is now available in preview, bringing more flexibility to database management. With the MySQL extension for Azure Data Studio, you can now connect to and modify MySQL databases, taking advantage of the modern editor experience and capabilities in Azure Data Studio. You can learn more here.

Announcing Azure SQL Database Offline Migrations in the Azure SQL Migration Extension (preview)

This new migration capability in the Azure SQL Migration extension provides an end-to-end experience to modernize from SQL Server to Azure SQL Database. This extension allows you to perform a migration readiness check with actions to remediate possible migration blockers, export the assessment results, and get right-sized Azure recommendations. These recommendations include an all-new elastic recommendation model to meet your database performance needs. Thanks to the Azure SQL Migration extension, you can perform offline migrations of your SQL Server databases running on-premises, SQL Server on Azure Virtual Machines, or any virtual machine running in the cloud (private, public) to Azure SQL Database. Learn more from this blog announcement. For a hands-on experience using this extension, please refer to the Migrate SQL Server to an Azure SQL Database offline using Azure Data Studio tutorial.

Query History Extension is now generally available

In the August release blog, we noted the benefits of the Query History extension which includes the ability to view previous queries executed and double-click on any query in the history to open it in a new window for viewing or execution. The team has addressed a few accessibility issues, added the ability to limit the number of entries stored, and it is now generally available through the extensions pane in Azure Data Studio. For those of you who write queries and tune code, the history provided from this extension can be a time-saver.

Visual Studio Code Merge—from 1.62 to 1.67

The UI framework of Azure Data Studio is forked from VS Code, and the codebase needs to be kept up to date with updates to its parent framework via merges, completed periodically by our engineers. This Azure Data Studio release includes updates that bring ADS to version 1.67, from its previous version, 1.62. While there are many updates in this release that users will appreciate, we have highlighted a few of our favorites below.

New Side Panel and Configure Layout settings 

Azure Data Studio now offers more flexibility to customize the layout in the user interface via the addition of Side Panels. With Side Panels, you can now house views from the Side Bar or the bottom Panel. Unlike moving the bottom Panel to the left or the right of the editor, the new Side Panel works in addition to the bottom Panel so you can see more sets of views at once. In the illustration below, the terminal is being dragged to the right and dropped to create the Side Panel. The user can then switch views in the Side Bar (by opening the global Search view), while keeping the terminal view visible.

To better configure layouts, we added a Customize Layout button in the title bar. This button provides a new interactive quick pick experience, allowing you to control all aspects of layout configuration in one place.

To learn more about these layout changes, check out the Visual Studio Code January 2022 release notes.

Local history

The local history of files is now available in the Timeline view. Every time you save a file in query editor, a new entry is added to the list. Each local history entry contains the full contents of the file at the time the entry was created and in certain cases, can provide more semantic information—for example, indicate a refactoring. In the illustration below, a CREATE TABLE T-SQL script is edited by inserting a statement to insert an additional column. Upon saving, this new entry is saved to the Local History tab and then compared to its previous version. You can also restore the content to previous versions, as well as delete or rename the entry. To learn more about this update, please check out this Visual Studio Code March 2022 release note.

Modified menu settings

The Settings editor search control now contains a funnel button on the right side. Clicking on the button shows a list of filters that you can apply to the search query to filter down the results.

Learn more

If you haven’t already installed this release of Azure Data Studio, please see how to on our download page.

The team is focused on improving Azure Data Studio from both a feature and stability perspective, and we hope these improvements make your daily use of ADS even better. 

We would love to hear your feedback on this release—you can find us on Twitter or log an issue on GitHub.

The post Azure Data Studio November release appeared first on Microsoft SQL Server Blog.

Part of the SQL Server 2022 blog series.

Traditionally, data to serve analytical systems have been extracted from operational data stores using custom-built extract, transform, and load (ETL) processes. These processes are often long-running, exert pressure on the source systems, and only run periodically in batch mode. While this kind of latency and overhead may be acceptable for some workloads, more and more companies are finding themselves in a place where they need to do analytics over operational data closer to real-time—something that traditional ETL systems cannot support.

Enter Azure Synapse Link for SQL.

Azure Synapse Link for SQL provides an automated way to extract data from source operational systems without having to build custom ETL processes. Some of the benefits of Azure Synapse Link for SQL are:

• Low code/no code solution: With Azure Synapse Link for SQL, you don’t need to build custom processes to extract the data and load it into an analytical system. You choose the tables that you want to replicate, specify how you want them stored in the target Azure Synapse Analytics dedicated SQL pool, and Azure Synapse Link for SQL takes care of the rest.
• Minimal impact on the source systems: We have strived to minimize the impact of data extraction from the source system. Where a traditional ETL process will run queries against the source tables, which can get expensive, Azure Synapse Link for SQL uses the new change feed functionality built into SQL Server 2022 and Azure SQL Database to get the data without having to run custom queries.
• Near-real-time data movement: Data is continually moved from the source systems into the Azure Synapse Analytics environment. Optionally, you can switch to “scheduled mode” if you don’t need near-real-time data movement.

How does it work?

Azure Synapse Link for SQL is powered by the new change feed functionality that has been added to SQL Server 2022 and Azure SQL Database. This functionality allows us to monitor tables for changes as they happen without the additional overhead that is brought along by a change data capture (CDC)–based data movement solution.

When a transaction is committed on a table that is being replicated by Azure Synapse Link for SQL, that transaction is written into a “landing zone,” which is a Gen2 Azure Data Lake storage (ADLS) account. From there, an ingestion service picks up the data and loads it into an Azure Synapse Analytics dedicated SQL pool. Once the data lands there, you can query the data like any other dedicated SQL pool.

Who will benefit?

Here are some examples of scenarios that would benefit from Azure Synapse Link for SQL:

• Database consolidation: Azure Synapse Link for SQL allows you to bring data from multiple source databases together into a single dedicated SQL pool for analytics. Whether you have multiple tenant databases that you want to use for market-based analytics, or you have grown by acquisition and have multiple source systems to bring together for analytics, Azure Synapse Link for SQL can bring all of that data together into a unified analytical platform.
• Hybrid on-premises/cloud: Since Azure Synapse Link for SQL supports both Azure SQL Database and SQL Server 2022, you can bring data into a common analytical system from wherever it lives.
• Near-real-time extension: If you have an ETL system that meets most of your needs but have a few tables where you want data to arrive closer to real-time, you could use Azure Synapse Link for SQL to transfer those tables from the source systems into the Azure Synapse Analytics dedicated SQL pool alongside the data that is processed in your nightly ETL system, and perform reporting an analytics tasks over all of the data.

How to learn more

• Read our technical blog post from the public preview launch.
• Check out our “getting started” documentation.
• Dig in with our How-To guides:
  • SQL Server 2022
  • Azure SQL Database

The post Azure Synapse Link for SQL appeared first on Microsoft SQL Server Blog.